AI and Sanctions Compliance - How Can it Help or Hurt Your Compliance Function?

AI is considered one of the technologies that can fundamentally change the banking industry, particularly Sanctions, but is this change a good or bad thing?  Well, for one AI can help banks with sanctions screening by helping to automate, optimize, and enhance their processes by using natural language processing, machine learning, and fuzzy matching to reduce false positives, flag high-risk cases, and identify complex patterns and networks of sanctions evasion. AI can also help financial institutions update and harmonize their screening rules and sources across different jurisdictions and regulations, and provide audit trails and explainable decisions. AI can even help financial institutions generate and update their compliance policies and procedures, and provide risk assessments and recommendations based on best practices and benchmarks.

However, there are also some potential drawbacks or challenges of using AI for these purposes, such as:

Reliability and accuracy: AI systems may not always be able to correctly identify or interpret complex or ambiguous data, such as names, addresses, or aliases that may vary across languages, cultures, or sources; or contextual factors, such as the purpose, origin, or destination of a transaction. AI systems may also make errors or biases due to faulty data, algorithms, or models, or lack of human oversight or feedback. These could result in false positives, false negatives, or inconsistent outcomes, which could expose the bank to regulatory, reputational, or legal risks, or harm legitimate customers or partners.

Transparency and explainability: AI systems may not always be able to provide clear and comprehensible explanations or justifications for their decisions or actions, especially if they rely on complex or opaque methods, such as deep learning or neural networks. This could pose challenges for financial institutions to ensure accountability, compliance, and trust, both internally and externally, and to respond to inquiries, audits, or disputes from regulators, customers, or stakeholders. It could also limit the bank's ability to monitor, review, or improve the performance or quality of the AI systems, or to identify and correct any errors or biases. Moreover, AI systems may not always respect or uphold the ethical principles or human rights standards that the bank or its customers or partners may expect or require, such as fairness, privacy, security, or non-discrimination.

Cost and complexity: AI systems may require significant investments in terms of resources, infrastructure, expertise, or maintenance, which may not always be feasible or affordable for the institution, especially if it operates in multiple or diverse jurisdictions or markets. AI systems may also introduce new or additional challenges or risks in terms of interoperability, compatibility, or integration with existing or legacy systems, processes, or standards, or with external or third-party data, platforms, or services. These could affect the efficiency, effectiveness, or security of the bank's operations, or create dependencies or vulnerabilities that could compromise its autonomy or resilience.

As AI systems may not always respect or uphold the ethical principles or human rights standards that the bank or its customers may expect or require, such as fairness, privacy, security, or non-discrimination, it must be used responsibly for bank compliance. This entails some challenges and risks, such as ensuring ethical, transparent, and accountable AI practices, protecting data privacy and security, and avoiding bias, discrimination, or harm to customers, employees, or stakeholders.

Compliance can benefit greatly from AI, but its adoption will be gradual. Compliance professionals have concerns and skepticism about AI. The effective and responsible use of technology in compliance depends on finding the right balance between AI-driven solutions and human expertise. This means we should be proactive in exploring AI's potential, while respecting the importance of human judgment and experience.